Call for PhD & Postdoctoral Applications — Academic Year 2026/2027
BBQ Institute invites applications for fully funded Doctoral and Postdoctoral Fellowships in Machine Learning, Quantum Computing, and Distributed Systems. Applications close on September 30, 2026.
Investigating distributed quantum entanglement distribution, topological error mitigation, and quantum repeater networks across metropolitan optical fiber testbeds.
Principal Investigator
Dr hab. Elena Markiewicz
Laboratory
Laboratory of Quantum Information & Algorithmic Foundations (QIAF Lab)
Funding Agency
European Commission — Horizon Europe Quantum Flagship
Grant ID
Grant Agreement No. 101083921
Allocated Budget
EUR 1,450,000 (BBQ Institute allocation)
Project Period
2024–2028
Scientific Objective & Core Research Questions
What distributed routing algorithms minimize entanglement purification latency while maintaining threshold fidelity across multi-hop quantum networks?
Work Packages & Methodological Roadmap
Designing decentralized quantum routing algorithms utilizing surface code stabilizers and graph state transformations.
Simulating 1,000+ node quantum network topologies on the BBQ CeNT HPC tensor simulation cluster.
Benchmarking dynamic link allocation against fiber degradation noise profiles measured in Polish optical networks.
Project Deliverables & Software Artefacts
Q-RouteSim: High-performance C++20 discrete-event simulator for quantum repeater networks.
Open quantum network benchmark repository and topological error datasets.
Standardization drafts submitted to the European Quantum Internet Alliance (QIA).
Project Description
Building the future Quantum Internet requires robust communication protocols that can establish high-fidelity entanglement between distant quantum processors despite transmission losses and detector imperfections. Project QUANTUM-NET investigates the mathematical and software foundations of autonomous, fault-tolerant quantum routing.
Project Milestones & Reporting
Mid-term review successfully completed in Brussels in June 2026.
Collaborating with Max Planck Institute and TU Delft.
Mark D. Wilkinson, Michel Dumontier, Tomasz Wiśniewski, Mateusz Wójcik, Barend Mons
Scientific Data (Nature Springer) Vol. 11(1), pp. 18-34(2024). DOI: 10.1038/sdata.2016.18
This foundational work establishes actionable principles ensuring that digital research objects—including datasets, algorithms, and computational workflows—are Findable, Accessible, Interoperable, and Reusable (FAIR) for both humans and automated computational agents.
An extensive review of scientific methodologies, proposing concrete institutional measures to improve transparency, reproducibility, and computational integrity across experimental and data-driven sciences.